The goal of this project is to propose and demonstrate schemes for data fusion from multiple sensors for the MRL algorithm, first proposed by Laufer Bracha, 2016 [1], in order to achieve a better and more noise-robust localization.
We first demonstrated the algorithm for a single sensor. Then, we proposed two fusion schemes for two sensors, demonstrated them and compared them. We found that sensor fusion is indeed quantitively useful, in terms of minimal RMSE. One of the proposed schemes has proven superior, both quantitively and qualitatively, then the other scheme.
We presented generalizations of these schemes to a general number of sensors, and tested them on a three-sensor system. The results were problematic. We suggested a hypothesis for the origin of this problem, and using this hypothesis were able to achieve meaningful results for one of the schemes.